Machine Learning systems are often distinguished according to the kind of representation they use, which can be either propositional or first-order logic. The framework working wi...
Teresa Maria Altomare Basile, Floriana Esposito, N...
We investigate methods for providing easy-to-check proofs of computational effort. Originally intended for discouraging spam, the concept has wide applicability as a method for co...
This paper describes ongoing research into the application of machine learning techniques for improving access to governmental information in complex digital libraries. Under the ...
Miles Efron, Jonathan L. Elsas, Gary Marchionini, ...
This paper is an analysis of two knowledge representation extensions of logic programming, namely Answer Set Programming and ID-Logic. Our aim is to compare both logics on the leve...
As modern embedded systems become more integrated and complex, it is crucial to be able to represent systems ple levels of abstraction, so that the design space can be effectively...
Xi Chen, Harry Hsieh, Felice Balarin, Yosinori Wat...